scholarly journals Simulation and Projection of Near-Surface Wind Speeds in China by BCC-CSM Models

2019 ◽  
Vol 33 (1) ◽  
pp. 149-158 ◽  
Author(s):  
Yajun Xiong ◽  
Xiaoge Xin ◽  
Xingxia Kou
Keyword(s):  
Surface Wind ◽  
Near Surface ◽  
Wind Speeds

Near-surface wind speeds in ERA5: Climatology, decadal variability and long-term trends

2021 ◽  
Author(s):  
Terhi K. Laurila ◽  
Victoria A. Sinclair ◽  
Hilppa Gregow
Keyword(s):  
Iberian Peninsula ◽  
North Atlantic ◽  
Decadal Variability ◽  
Surface Wind ◽  
Northern Europe ◽  
Near Surface ◽  
Wind Speeds ◽  
The North ◽  
The North Atlantic

<p>The knowledge of long-term climate and variability of near-surface wind speeds is essential and widely used among meteorologists, climate scientists and in industries such as wind energy and forestry. The new high-resolution ERA5 reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) will likely be used as a reference in future climate projections and in many wind-related applications. Hence, it is important to know what is the mean climate and variability of wind speeds in ERA5.</p><p>We present the monthly 10-m wind speed climate and decadal variability in the North Atlantic and Europe during the 40-year period (1979-2018) based on ERA5. In addition, we examine temporal time series and possible trends in three locations: the central North Atlantic, Finland and Iberian Peninsula. Moreover, we investigate what are the physical reasons for the decadal changes in 10-m wind speeds.</p><p>The 40-year mean and the 98th percentile wind speeds show a distinct contrast between land and sea with the strongest winds over the ocean and a seasonal variation with the strongest winds during winter time. The winds have the highest values and variabilities associated with storm tracks and local wind phenomena such as the mistral. To investigate the extremeness of the winds, we defined an extreme find factor (EWF) which is the ratio between the 98th percentile and mean wind speeds. The EWF is higher in southern Europe than in northern Europe during all months. Mostly no statistically significant linear trends of 10-m wind speeds were found in the 40-year period in the three locations and the annual and decadal variability was large.</p><p>The windiest decade in northern Europe was the 1990s and in southern Europe the 1980s and 2010s. The decadal changes in 10-m wind speeds were largely explained by the position of the jet stream and storm tracks and the strength of the north-south pressure gradient over the North Atlantic. In addition, we investigated the correlation between the North Atlantic Oscillation (NAO) and the Atlantic Multi-decadal Oscillation (AMO) in the three locations. The NAO has a positive correlation in the central North Atlantic and Finland and a negative correlation in Iberian Peninsula. The AMO correlates moderately with the winds in the central North Atlantic but no correlation was found in Finland or the Iberian Peninsula. Overall, our study highlights that rather than just using long-term linear trends in wind speeds it is more informative to consider inter-annual or decadal variability.</p>

scholarly journals At What Time of Day Do Daily Extreme Near-Surface Wind Speeds Occur?

2014 ◽  
Vol 27 (11) ◽  
pp. 4226-4244 ◽  
Author(s):  
Robert Fajber ◽  
Adam H. Monahan ◽  
William J. Merryfield
Keyword(s):  
Extreme Values ◽  
Mechanistic Model ◽  
Surface Wind ◽  
Time Of Day ◽  
Near Surface ◽  
Wind Speeds ◽  
Boundary Layer Processes ◽  
Early Afternoon ◽  
Extreme Wind ◽  
Extreme Wind Speeds

Abstract The timing of daily extreme wind speeds from 10 to 200 m is considered using 11 yr of 10-min averaged data from the 213-m tower at Cabauw, the Netherlands. This analysis is complicated by the tendency of autocorrelated time series to take their extreme values near the beginning or end of a fixed window in time, even when the series is stationary. It is demonstrated that a simple averaging procedure using different base times to define the day effectively suppresses this “edge effect” and enhances the intrinsic nonstationarity associated with diurnal variations in boundary layer processes. It is found that daily extreme wind speeds at 10 m are most likely in the early afternoon, whereas those at 200 m are most likely in between midnight and sunrise. An analysis of the joint distribution of the timing of extremes at these two altitudes indicates the presence of two regimes: one in which the timing is synchronized between these two layers, and the other in which the occurrence of extremes is asynchronous. These results are interpreted physically using an idealized mechanistic model of the surface layer momentum budget.

scholarly journals Gust Factors and Turbulence Intensities for the Tropical Cyclone Environment

2009 ◽  
Vol 48 (3) ◽  
pp. 534-552 ◽  
Author(s):  
Bo Yu ◽  
Arindam Gan Chowdhury
Keyword(s):  
Tropical Cyclone ◽  
Surface Wind ◽  
Monitoring Program ◽  
Near Surface ◽  
Wind Speeds ◽  
Flat Terrain ◽  
Short Period ◽  
Terrain Roughness ◽  
American Society ◽  
Gust Factors

Abstract Gust factors are used to convert peak wind speeds averaged over a relatively short period (e.g., 3 s) to mean wind speeds averaged over a relatively long reference period (e.g., 1 h) or vice versa. Such conversions are needed for engineering, climatological, or forecasting purposes. In this paper, gust factors in tropical cyclone (TC) winds are estimated from Florida Coastal Monitoring Program (FCMP) observations of near-surface TC wind speeds representative of flow over the sea surface and over open flat terrain in coastal areas. Comparisons are made with gust factors in extratropical winds over open flat terrain that are available in the literature. According to the results of the study, for gust durations of less than 20 s, the Durst model underestimates, and the Krayer–Marshall model overestimates, gust factors of TC winds over surfaces with roughness specified in the American Society of Civil Engineers (ASCE) 7 Standard Commentary as typical of open terrain. Consideration should be given to these findings when updating the gust factors provided in the ASCE 7 Standard Commentary. The study also compares gust factors in TC winds obtained from FCMP data with gust factors in extratropical winds obtained from near-surface wind data collected at eight Automated Surface Observing System (ASOS) stations and concludes that, depending upon terrain roughness, gust factors in TC winds can be higher by about 10%–15% than gust factors in extratropical winds. The study also presents FCMP-based estimates of turbulence intensities and their variability and shows that turbulence intensities in TC winds increase as the terrain roughness increases. The longitudinal turbulence intensity can vary from storm to storm and can exceed its typical value by as much as 20%. It is recommended that future TC wind measurement campaigns obtain temperature data usable for stratification estimation purposes, as well as information on waves and storm surge upwind of the anemometer towers.

scholarly journals Comparison of regional and global reanalysis near-surface winds with station observations over Germany

2015 ◽  
Vol 12 (1) ◽  
pp. 187-198 ◽  
Author(s):  
A. K. Kaiser-Weiss ◽  
F. Kaspar ◽  
V. Heene ◽  
M. Borsche ◽  
D. G. H. Tan ◽  
...  
Keyword(s):  
Information Source ◽  
Surface Wind ◽  
Wind Fields ◽  
Near Surface ◽  
Wind Speeds ◽  
Energy Applications ◽  
The North ◽  
Independent Observations ◽  
Spatio Temporal ◽  
The North Atlantic Oscillation

Abstract. Reanalysis near-surface wind fields from multiple reanalyses are potentially an important information source for wind energy applications. Inter-comparing reanalyses via employing independent observations can help to guide users to useful spatio-temporal scales. Here we compare the statistical properties of wind speeds observed at 210 traditional meteorological stations over Germany with the reanalyses' near-surface fields, confining the analysis to the recent years (2007 to 2010). In this period, the station time series in Germany can be expected to be mostly homogeneous. We compare with a regional reanalysis (COSMO-REA6) and two global reanalyses, ERA-Interim and ERA-20C. We show that for the majority of the stations, the Weibull parameters of the daily mean wind speed frequency distribution match remarkably well with the ones derived from the reanalysis fields. High correlations (larger than 0.9) can be found between stations and reanalysis monthly mean wind speeds all over Germany. Generally, the correlation between the higher resolved COSMO-REA6 wind fields and station observations is highest, for both assimilated and non-assimilated (i.e., independent) observations. As expected from the lower spatial resolution and reduced amount of data assimilated into ERA-20C, the correlation of monthly means decreases somewhat relative to the other reanalyses (in our investigated period of 2007 to 2010). Still, the inter-annual variability connected to the North Atlantic Oscillation (NAO) found in the reanalysis surface wind anomalies is in accordance with the anomalies recorded by the stations. We discuss some typical examples where differences are found, e.g., where the mean wind distributions differ (probably related to either height or model topography differences) and where the correlations break down (because of unresolved local topography) which applies to a minority of stations. We also identified stations with homogeneity problems in the reported station values, demonstrating how reanalyses can be applied to support quality control for the observed station data. Finally, as a demonstration of concept, we discuss how comparing feedback files of the different reanalyses can guide users to useful scales of variability.

scholarly journals CYGNSS Ocean Surface Wind Validation in the Tropics

2020 ◽  
Author(s):  
Shakeel Asharaf ◽  
Duane E. Waliser ◽  
Derek J. Posselt ◽  
Christopher S. Ruf ◽  
Chidong Zhang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Satellite System ◽  
Cold Pool ◽  
Tropical Ocean ◽  
Near Surface ◽  
Wind Speeds ◽  
Low Wind Speeds ◽  
Global Navigation Satellite

AbstractSurface wind plays a crucial role in many local/regional weather and climate processes, especially through the exchanges of energy, mass and momentum across the Earth’s surface. However, there is a lack of consistent observations with continuous coverage over the global tropical ocean. To fill this gap, the NASA Cyclone Global Navigation Satellite System (CYGNSS) mission was launched in December 2016, consisting of a constellation of eight small spacecrafts that remotely sense near surface wind speed over the tropical and sub-tropical oceans with relatively high sampling rates both temporally and spatially. This current study uses data obtained from the Tropical Moored Buoy Arrays to quantitatively characterize and validate the CYGNSS derived winds over the tropical Indian, Pacific, and Atlantic Oceans. The validation results show that the uncertainty in CYGNSS wind speed, as compared with these tropical buoy data, is less than 2 m s-1 root mean squared difference, meeting the NASA science mission Level-1 uncertainty requirement for wind speeds below 20 m s-1. The quality of the CYGNSS wind is further assessed under different precipitation conditions, and in convective cold-pool events, identified using buoy rain and temperature data. Results show that CYGNSS winds compare fairly well with buoy observations in the presence of rain, though at low wind speeds the presence of rain appears to cause a slight positive wind speed bias in the CYGNSS data. The comparison indicates the potential utility of the CYGNSS surface wind product, which in turn may help to unravel the complexities of air-sea interaction in regions that are relatively under-sampled by other observing platforms.

scholarly journals An Assessment of NASA’s GMAO MERRA-2 Reanalysis Surface Winds

2019 ◽  
Vol 32 (23) ◽  
pp. 8261-8281 ◽  
Author(s):  
D. Carvalho
Keyword(s):  
Surface Wind ◽  
The Other ◽  
Surface Winds ◽  
Wind Fields ◽  
Near Surface ◽  
Wind Speeds ◽  
Wide Range ◽  
Ocean Surface Winds ◽  
The Tropics ◽  
Global Surface

Abstract The quality of MERRA-2 surface wind fields was assessed by comparing them with 10 years of measurements from a wide range of surface wind observing platforms. This assessment includes a comparison of MERRA-2 global surface wind fields with the ones from its predecessor, MERRA, to assess if GMAO’s latest reanalyses improved the representation of the global surface winds. At the same time, surface wind fields from other modern reanalyses—NCEP-CFSR, ERA-Interim, and JRA-55—were also included in the comparisons to evaluate MERRA-2 global surface wind fields in the context of its contemporary reanalyses. Results show that MERRA-2, CFSR, ERA-Interim, and JRA-55 show similar error metrics while MERRA consistently shows the highest errors. Thus, when compared with wind observations, the accuracy of MERRA-2 surface wind fields represents a clear improvement over its predecessor MERRA and is in line with the other contemporary reanalyses in terms of the representation of global near-surface wind fields. All reanalyses showed a tendency to underestimate ocean surface winds (particularly in the tropics) and, oppositely, to overestimate inland surface winds (except JRA-55, which showed a global tendency to underestimate the wind speeds); to represent the wind direction rotated clockwise in the Northern Hemisphere (positive bias) and anticlockwise in the Southern Hemisphere (negative bias), with the exception of JRA-55; and to show higher errors near the poles and in the ITCZ, particularly in the equatorial western coasts of Central America and Africa. However, MERRA-2 showed substantially lower wind errors in the poles when compared with the other reanalyses.

scholarly journals High-resolution observations of the near-surface wind field over an isolated mountain and in a steep river canyon

2015 ◽  
Vol 15 (7) ◽  
pp. 3785-3801 ◽  
Author(s):  
B. W. Butler ◽  
N. S. Wagenbrenner ◽  
J. M. Forthofer ◽  
B. K. Lamb ◽  
K. S. Shannon ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Surface Wind ◽  
Wind Data ◽  
Wind Flow ◽  
Surface Winds ◽  
Mean Flow ◽  
Near Surface ◽  
Wind Speeds ◽  
Synoptic Forcing

Abstract. A number of numerical wind flow models have been developed for simulating wind flow at relatively fine spatial resolutions (e.g., ~ 100 m); however, there are very limited observational data available for evaluating these high-resolution models. This study presents high-resolution surface wind data sets collected from an isolated mountain and a steep river canyon. The wind data are presented in terms of four flow regimes: upslope, afternoon, downslope, and a synoptically driven regime. There were notable differences in the data collected from the two terrain types. For example, wind speeds on the isolated mountain increased with distance upslope during upslope flow, but generally decreased with distance upslope at the river canyon site during upslope flow. In a downslope flow, wind speed did not have a consistent trend with position on the isolated mountain, but generally increased with distance upslope at the river canyon site. The highest measured speeds occurred during the passage of frontal systems on the isolated mountain. Mountaintop winds were often twice as high as wind speeds measured on the surrounding plain. The highest speeds measured in the river canyon occurred during late morning hours and were from easterly down-canyon flows, presumably associated with surface pressure gradients induced by formation of a regional thermal trough to the west and high pressure to the east. Under periods of weak synoptic forcing, surface winds tended to be decoupled from large-scale flows, and under periods of strong synoptic forcing, variability in surface winds was sufficiently large due to terrain-induced mechanical effects (speed-up over ridges and decreased speeds on leeward sides of terrain obstacles) that a large-scale mean flow would not be representative of surface winds at most locations on or within the terrain feature. These findings suggest that traditional operational weather model (i.e., with numerical grid resolutions of around 4 km or larger) wind predictions are not likely to be good predictors of local near-surface winds on sub-grid scales in complex terrain. Measurement data can be found at http://www.firemodels.org/index.php/windninja-introduction/windninja-publications.

scholarly journals Estimation of near surface wind speeds in strongly rotating flows

2014 ◽  
Vol 235 ◽  
pp. 201-211
Author(s):  
Sean Crowell ◽  
Luther White ◽  
Louis Wicker
Keyword(s):  
Surface Wind ◽  
Rotating Flows ◽  
Near Surface ◽  
Wind Speeds

scholarly journals A Global Climatology of Wind–Wave Interaction

2010 ◽  
Vol 40 (6) ◽  
pp. 1263-1282 ◽  
Author(s):  
Kirsty E. Hanley ◽  
Stephen E. Belcher ◽  
Peter P. Sullivan
Keyword(s):  
Surface Wind ◽  
Ocean Waves ◽  
Wave Age ◽  
Local Wind ◽  
Wind Regime ◽  
Wave Regime ◽  
Near Surface ◽  
Wave Fields ◽  
Wind Speeds ◽  
The Waves

Abstract Generally, ocean waves are thought to act as a drag on the surface wind so that momentum is transferred downward, from the atmosphere into the waves. Recent observations have suggested that when long wavelength waves—which are characteristic of remotely generated swell—propagate faster than the surface wind, momentum can also be transferred upward. This upward momentum transfer acts to accelerate the near-surface wind, resulting in a low-level wave-driven wind jet. Previous studies have suggested that the sign reversal of the momentum flux is well predicted by the inverse wave age, the ratio of the surface wind speed to the speed of the waves at the peak of the spectrum. Data from the 40-yr ECMWF Re-Analysis (ERA-40) have been used here to calculate the global distribution of the inverse wave age to determine whether there are regions of the ocean that are usually in the wind-driven wave regime and others that are generally in the wave-driven wind regime. The wind-driven wave regime is found to occur most often in the midlatitude storm tracks where wind speeds are generally high. The wave-driven wind regime is found to be prevalent in the tropics where wind speeds are generally light and swell can propagate from storms at higher latitudes. The inverse wave age is also a useful indicator of the degree of coupling between the local wind and wave fields. The climatologies presented emphasize the nonequilibrium that exists between the local wind and wave fields and highlight the importance of swell in the global oceans.

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